diff --git a/src/f3dasm/_src/datageneration/datagenerator.py b/src/f3dasm/_src/datageneration/datagenerator.py
index 335f5465..93d421f5 100644
--- a/src/f3dasm/_src/datageneration/datagenerator.py
+++ b/src/f3dasm/_src/datageneration/datagenerator.py
@@ -7,6 +7,7 @@
 
 # Standard
 import sys
+from abc import abstractmethod
 from functools import partial
 from typing import Any, Callable
 
@@ -43,30 +44,80 @@ class DataGenerator:
     """Base class for a data generator"""
 
     def pre_process(self, experiment_sample: ExperimentSample, **kwargs) -> None:
-        """Function that handles the pre-processing"""
+        """Interface function that handles the pre-processing of the data generator
+
+        Notes
+        -----
+        If not implemented the function will be skipped
+
+        The experiment_sample is cached inside the data generator. This
+        allows the user to access the experiment_sample in the pre_process, execute
+        and post_process functions as a class variable called self.experiment_sample.
+        """
         ...
 
+    @abstractmethod
     def execute(self, **kwargs) -> None:
-        """Function that calls the FEM simulator the pre-processing"""
-        raise NotImplementedError("No execute function implemented!")
+        """Interface function that handles the execution of the data generator
+
+        Raises
+        ------
+        NotImplementedError
+            If the function is not implemented by the user
+
+        Notes
+        -----
+        The experiment_sample is cached inside the data generator. This
+        allows the user to access the experiment_sample in the pre_process, execute
+        and post_process functions as a class variable called self.experiment_sample.
+        """
+
+        ...
 
     def post_process(self, experiment_sample: ExperimentSample, **kwargs) -> None:
-        """Function that handles the post-processing"""
+        """Interface function that handles the post-processing of the data generator
+
+        Notes
+        -----
+        If not implemented the function will be skipped
+
+        The experiment_sample is cached inside the data generator. This
+        allows the user to access the experiment_sample in the pre_process, execute
+        and post_process functions as a class variable called self.experiment_sample.
+        """
         ...
 
     @time_and_log
     def _run(self, experiment_sample: ExperimentSample, **kwargs) -> ExperimentSample:
-        """Run the data generator
+        """
+        Run the data generator
+        This function chains the following methods together
+
+        * pre_process(); to combine the experiment_sample and the parameters
+        of the data generator to an input file that can be used to run the data generator
+
+        * execute(); to run the data generator and generate the response of the experiment
+
+        * post_process(); to process the response of the experiment and store it back
+         in the experiment_sample
+
+        The function also caches the experiment_sample in the data generator. This
+        allows the user to access the experiment_sample in the pre_process, execute
+        and post_process functions as a class variable called self.experiment_sample.
 
         Parameters
         ----------
         ExperimentSample : ExperimentSample
             The design to run the data generator on
 
+        kwargs : dict
+            The keyword arguments to pass to the pre_process, execute and post_process
+
         Returns
         -------
         ExperimentSample
-            Processed design
+            Processed design with the response of the data generator saved in the
+            experiment_sample
         """
         # Cache the design
         self.experiment_sample: ExperimentSample = experiment_sample
@@ -88,7 +139,25 @@ def _post_simulation(self) -> None:
         ...
 
     def add_pre_process(self, func: Callable, **kwargs):
+        """Add a pre-processing function to the data generator
+
+        Parameters
+        ----------
+        func : Callable
+            The function to add to the pre-processing
+        kwargs : dict
+            The keyword arguments to pass to the pre-processing function
+        """
         self.pre_process = partial(func, **kwargs)
 
     def add_post_process(self, func: Callable, **kwargs):
+        """Add a post-processing function to the data generator
+
+        Parameters
+        ----------
+        func : Callable
+            The function to add to the post-processing
+        kwargs : dict
+            The keyword arguments to pass to the post-processing function
+        """
         self.post_process = partial(func, **kwargs)